Operations | Monitoring | ITSM | DevOps | Cloud

Today’s AI agents have grown increasingly sophisticated, moving into production environments and becoming integral parts of engineering workflows. But these agents can also be black boxes for engineers, which makes observability more critical than ever. Without proper monitoring, you’re often left feeling like you’re flying blind as you try to debug agent failures, understand performance bottlenecks, and track costs.

Nishad Krishnan is a Software Engineer at Temporal Technologies, where he’s focused on observability and making the “unknown unknowns” slightly less unknown. At Temporal Technologies, our goal is to make it easier for developers to build and operate reliable, scalable applications without sacrificing productivity. Our platform, Temporal, helps ensure that code runs to completion once started, no matter how long it takes or what failures occur along the way.

Grafana is great at hopping between signals in its native backends (Grafana Loki, Grafana Mimir, Grafana Tempo). But your data doesn’t have to live there to get the same smooth workflow. Afterall, we don’t just pay lip service to our “big tent” philosophy—we want to meet all our users’ diverse needs, regardless of what kind of data you have or where you store it.

Grafana 12.3 is here, delivering new features for interactive learning, deeper insights into logging data, and so much more. Overall, a big theme in the latest minor release is to make data exploration easier, faster, and more customizable. Grafana 12.3: Download now! Below are just some of the highlights from Grafana 12.3. If you want to explore all the latest updates, please refer to the changelog or our What’s New documentation, and be sure to check out the TL;DR video below.

Our logs can tell us so much about the state of our systems, but they can also be a bit overwhelming. Yes, Grafana Loki—and, by extension, Grafana Cloud Logs, which is powered by Loki—reimagined the way log aggregation systems could meet modern engineering demands, but logs, by their very nature, are still voluminous.

Editor’s note: This blog originally published in May 2025 when Azure Monitor dashboards with Grafana became available in public preview. It was updated in November 2025 to reflect general availability. The Grafanaverse just got a little bit bigger.

About two months ago, an incident at Grafana Labs was kicked off in typical fashion: A series of alerts were triggered, our on-call engineer acknowledged it on Slack, and the rest of the team quickly began hypothesizing about the potential culprit. But the way the incident was resolved was anything but typical. Yes, our internal team followed best practices to resolve the incident as quickly as possible.

Grafana Play is a free, publicly accessible sandbox environment where anyone can explore and learn about Grafana, no setup or sign-in required. It comes preloaded with sample dashboards demonstrating how to connect to data sources, build visualizations, and experiment with Grafana’s advanced features. Hosted on Grafana Cloud, Grafana Play has grown significantly over the years. With thousands of public dashboards, it’s now a go-to destination for Grafana learning and exploration.

It’s widely acknowledged that most application performance problems stem not from the application itself, but from the underlying database. Slow or inefficient database queries are often the primary cause of these issues, acting as the biggest driver of application performance incidents. If you’ve been troubleshooting slow API calls or sluggish services, chances are the root cause likely resides within your database layer.

For many organizations, periods of high customer activity are anything but relaxing. Events like Black Friday, product launches, or major sales can put intense strain on the software and infrastructure systems that support a company’s web applications. Without proactive performance testing, these moments can quickly turn into poor user experiences and lost revenue.